Organizations are relying more and more on distributed, cloud-native ecosystems to give users smooth digital experiences. However, traditional orchestration solutions have trouble managing these resources that are spread out, performance that is inconsistent as well as adapting to changes in actual time. This research presents an AI-driven multi-cloud orchestration solution designed to unify provisioning, scaling, optimization along with their experience monitoring across various cloud environments, emphasizing customer-centric Key Experience Indicators. The proposed architecture combines intent-driven automation, predictive analytics, deep reinforcement learning & cross-cloud telemetry fusion to dynamically allocate these resources, find problems, predict performance drops, & fix them on their own before they affect end users. To fix the ongoing gap between infrastructure automation and providing a good digital experience, the solution gives equal weight to application-level responsiveness, user journey continuity & cost-performance trade-offs. The evaluation employed a combination of authentic enterprise workloads, artificial stress tests, and multi-cloud settings spa
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